Winston Artory Group

Data Engineer

• Build the data team from scratch —define the hiring roadmap, recruit and onboard your first 2–3 data engineers, and establish the team’s culture, standards, and ways of working
• Own the entire data platform architecture from day one—make the critical decisions on storage layers, processing frameworks, orchestration, and data modeling patterns
• Define technical standards and best practices for data quality, testing, documentation, lineage, and governance
• Lead system design for complex problems involving large-scale ingestion, entity resolution, LLM-powered data extraction, and real-time analytics
• Evaluate and adopt new technologies that improve data velocity, quality, reliability, or capabilities
• Establish data governance frameworks including versioning, reproducibility, validation, and compliance
• Design and operate scalable data ingestion and web scraping systems, including best practices around retries, proxies, rate limiting, and anti-bot strategies
• Build batch and real-time pipelines to normalize, enrich, deduplicate, and version data across structured and unstructured sources
• Architect systems to support LLM- and ML-based document parsing, OCR, entity extraction, and classification at scale
• Own the data storage and processing stack, including PostgreSQL, data lakes, data warehouses, and vector databases
• Operationalize AI/ML workflows by preparing clean training and inference datasets with robust lineage, validation, and error handling
• Design and maintain data models that serve backend APIs, valuation services, analytics dashboards, and public indices
• Contribute to infrastructure tooling, including CI/CD, IaC (Terraform), data observability, and cost management
• Co-own data platform vision with Head of Engineering: collaborate daily on architecture, technical roadmap, and engineering standards
• Partner with backend engineers to define API contracts, data serving patterns, and integration points between pipelines and application services
• Collaborate with product and domain experts to translate business requirements into reliable, well-modeled datasets
• Work with company leadership (Head of Engineering, CPO, President) on data strategy, hiring, and long-term platform vision
• Communicate technical decisions clearly to non-technical stakeholders

Staff Data Engineer